R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(93.0,0,99.2,0,112.2,0,112.1,0,103.3,0,108.2,0,90.4,0,72.8,0,111.0,0,117.9,0,111.3,0,110.5,0,94.8,0,100.4,0,132.1,0,114.6,0,101.9,0,130.2,0,84.0,0,86.4,0,122.3,0,120.9,0,110.2,0,112.6,0,102.0,0,105.0,0,130.5,0,115.5,0,103.7,0,130.9,0,89.1,0,93.8,0,123.8,0,111.9,0,118.3,0,116.9,0,103.6,1,116.6,1,141.3,1,107.0,1,125.2,1,136.4,1,91.6,1,95.3,1,132.3,1,130.6,1,131.9,1,118.6,1,114.3,1,111.3,1,126.5,1,112.1,1,119.3,1,142.4,1,101.1,1,97.4,1,129.1,1,136.9,1,129.8,1,123.9,1),dim=c(2,60),dimnames=list(c('INV','INVA'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('INV','INVA'),1:60))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
INV INVA M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 93.0 0 1 0 0 0 0 0 0 0 0 0 0
2 99.2 0 0 1 0 0 0 0 0 0 0 0 0
3 112.2 0 0 0 1 0 0 0 0 0 0 0 0
4 112.1 0 0 0 0 1 0 0 0 0 0 0 0
5 103.3 0 0 0 0 0 1 0 0 0 0 0 0
6 108.2 0 0 0 0 0 0 1 0 0 0 0 0
7 90.4 0 0 0 0 0 0 0 1 0 0 0 0
8 72.8 0 0 0 0 0 0 0 0 1 0 0 0
9 111.0 0 0 0 0 0 0 0 0 0 1 0 0
10 117.9 0 0 0 0 0 0 0 0 0 0 1 0
11 111.3 0 0 0 0 0 0 0 0 0 0 0 1
12 110.5 0 0 0 0 0 0 0 0 0 0 0 0
13 94.8 0 1 0 0 0 0 0 0 0 0 0 0
14 100.4 0 0 1 0 0 0 0 0 0 0 0 0
15 132.1 0 0 0 1 0 0 0 0 0 0 0 0
16 114.6 0 0 0 0 1 0 0 0 0 0 0 0
17 101.9 0 0 0 0 0 1 0 0 0 0 0 0
18 130.2 0 0 0 0 0 0 1 0 0 0 0 0
19 84.0 0 0 0 0 0 0 0 1 0 0 0 0
20 86.4 0 0 0 0 0 0 0 0 1 0 0 0
21 122.3 0 0 0 0 0 0 0 0 0 1 0 0
22 120.9 0 0 0 0 0 0 0 0 0 0 1 0
23 110.2 0 0 0 0 0 0 0 0 0 0 0 1
24 112.6 0 0 0 0 0 0 0 0 0 0 0 0
25 102.0 0 1 0 0 0 0 0 0 0 0 0 0
26 105.0 0 0 1 0 0 0 0 0 0 0 0 0
27 130.5 0 0 0 1 0 0 0 0 0 0 0 0
28 115.5 0 0 0 0 1 0 0 0 0 0 0 0
29 103.7 0 0 0 0 0 1 0 0 0 0 0 0
30 130.9 0 0 0 0 0 0 1 0 0 0 0 0
31 89.1 0 0 0 0 0 0 0 1 0 0 0 0
32 93.8 0 0 0 0 0 0 0 0 1 0 0 0
33 123.8 0 0 0 0 0 0 0 0 0 1 0 0
34 111.9 0 0 0 0 0 0 0 0 0 0 1 0
35 118.3 0 0 0 0 0 0 0 0 0 0 0 1
36 116.9 0 0 0 0 0 0 0 0 0 0 0 0
37 103.6 1 1 0 0 0 0 0 0 0 0 0 0
38 116.6 1 0 1 0 0 0 0 0 0 0 0 0
39 141.3 1 0 0 1 0 0 0 0 0 0 0 0
40 107.0 1 0 0 0 1 0 0 0 0 0 0 0
41 125.2 1 0 0 0 0 1 0 0 0 0 0 0
42 136.4 1 0 0 0 0 0 1 0 0 0 0 0
43 91.6 1 0 0 0 0 0 0 1 0 0 0 0
44 95.3 1 0 0 0 0 0 0 0 1 0 0 0
45 132.3 1 0 0 0 0 0 0 0 0 1 0 0
46 130.6 1 0 0 0 0 0 0 0 0 0 1 0
47 131.9 1 0 0 0 0 0 0 0 0 0 0 1
48 118.6 1 0 0 0 0 0 0 0 0 0 0 0
49 114.3 1 1 0 0 0 0 0 0 0 0 0 0
50 111.3 1 0 1 0 0 0 0 0 0 0 0 0
51 126.5 1 0 0 1 0 0 0 0 0 0 0 0
52 112.1 1 0 0 0 1 0 0 0 0 0 0 0
53 119.3 1 0 0 0 0 1 0 0 0 0 0 0
54 142.4 1 0 0 0 0 0 1 0 0 0 0 0
55 101.1 1 0 0 0 0 0 0 1 0 0 0 0
56 97.4 1 0 0 0 0 0 0 0 1 0 0 0
57 129.1 1 0 0 0 0 0 0 0 0 1 0 0
58 136.9 1 0 0 0 0 0 0 0 0 0 1 0
59 129.8 1 0 0 0 0 0 0 0 0 0 0 1
60 123.9 1 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) INVA M1 M2 M3 M4
111.86 11.61 -14.96 -10.00 12.02 -4.24
M5 M6 M7 M8 M9 M10
-5.82 13.12 -25.26 -27.36 7.20 7.14
M11
3.80
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-16.775 -3.025 1.019 4.661 9.305
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 111.855 2.952 37.892 < 2e-16 ***
INVA 11.613 1.693 6.859 1.34e-08 ***
M1 -14.960 4.063 -3.682 0.000597 ***
M2 -10.000 4.063 -2.461 0.017582 *
M3 12.020 4.063 2.958 0.004832 **
M4 -4.240 4.063 -1.043 0.302064
M5 -5.820 4.063 -1.432 0.158669
M6 13.120 4.063 3.229 0.002269 **
M7 -25.260 4.063 -6.217 1.26e-07 ***
M8 -27.360 4.063 -6.733 2.08e-08 ***
M9 7.200 4.063 1.772 0.082886 .
M10 7.140 4.063 1.757 0.085400 .
M11 3.800 4.063 0.935 0.354469
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.425 on 47 degrees of freedom
Multiple R-squared: 0.8619, Adjusted R-squared: 0.8266
F-statistic: 24.43 on 12 and 47 DF, p-value: 3.339e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.9156784 0.16864327 0.08432163
[2,] 0.8586807 0.28263850 0.14131925
[3,] 0.9787056 0.04258884 0.02129442
[4,] 0.9659893 0.06802147 0.03401073
[5,] 0.9704536 0.05909288 0.02954644
[6,] 0.9651838 0.06963247 0.03481623
[7,] 0.9400787 0.11984261 0.05992131
[8,] 0.9360055 0.12798901 0.06399450
[9,] 0.8988734 0.20225316 0.10112658
[10,] 0.8759220 0.24815607 0.12407803
[11,] 0.8303883 0.33922333 0.16961166
[12,] 0.8108235 0.37835303 0.18917652
[13,] 0.8770123 0.24597532 0.12298766
[14,] 0.8682635 0.26347297 0.13173649
[15,] 0.8648231 0.27035389 0.13517695
[16,] 0.8080065 0.38398700 0.19199350
[17,] 0.8621532 0.27569361 0.13784680
[18,] 0.8368120 0.32637595 0.16318798
[19,] 0.8818837 0.23623262 0.11811631
[20,] 0.8655980 0.26880391 0.13440196
[21,] 0.8061471 0.38770589 0.19385295
[22,] 0.8228838 0.35423234 0.17711617
[23,] 0.7775290 0.44494207 0.22247103
[24,] 0.9154183 0.16916334 0.08458167
[25,] 0.9220993 0.15580149 0.07790074
[26,] 0.9126397 0.17472053 0.08736026
[27,] 0.8812534 0.23749325 0.11874663
[28,] 0.9287614 0.14247724 0.07123862
[29,] 0.8398318 0.32033640 0.16016820
> postscript(file="/var/www/html/rcomp/tmp/1zixj1229619353.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ztyx1229619353.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/38w6v1229619353.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4y5my1229619353.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/56k6m1229619353.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 60
Frequency = 1
1 2 3 4 5 6 7 8
-3.8950 -2.6550 -11.6750 4.4850 -2.7350 -16.7750 3.8050 -11.6950
9 10 11 12 13 14 15 16
-8.0550 -1.0950 -4.3550 -1.3550 -2.0950 -1.4550 8.2250 6.9850
17 18 19 20 21 22 23 24
-4.1350 5.2250 -2.5950 1.9050 3.2450 1.9050 -5.4550 0.7450
25 26 27 28 29 30 31 32
5.1050 3.1450 6.6250 7.8850 -2.3350 5.9250 2.5050 9.3050
33 34 35 36 37 38 39 40
4.7450 -7.0950 2.6450 5.0450 -4.9075 3.1325 5.8125 -12.2275
41 42 43 44 45 46 47 48
7.5525 -0.1875 -6.6075 -0.8075 1.6325 -0.0075 4.6325 -4.8675
49 50 51 52 53 54 55 56
5.7925 -2.1675 -8.9875 -7.1275 1.6525 5.8125 2.8925 1.2925
57 58 59 60
-1.5675 6.2925 2.5325 0.4325
> postscript(file="/var/www/html/rcomp/tmp/6quk11229619353.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -3.8950 NA
1 -2.6550 -3.8950
2 -11.6750 -2.6550
3 4.4850 -11.6750
4 -2.7350 4.4850
5 -16.7750 -2.7350
6 3.8050 -16.7750
7 -11.6950 3.8050
8 -8.0550 -11.6950
9 -1.0950 -8.0550
10 -4.3550 -1.0950
11 -1.3550 -4.3550
12 -2.0950 -1.3550
13 -1.4550 -2.0950
14 8.2250 -1.4550
15 6.9850 8.2250
16 -4.1350 6.9850
17 5.2250 -4.1350
18 -2.5950 5.2250
19 1.9050 -2.5950
20 3.2450 1.9050
21 1.9050 3.2450
22 -5.4550 1.9050
23 0.7450 -5.4550
24 5.1050 0.7450
25 3.1450 5.1050
26 6.6250 3.1450
27 7.8850 6.6250
28 -2.3350 7.8850
29 5.9250 -2.3350
30 2.5050 5.9250
31 9.3050 2.5050
32 4.7450 9.3050
33 -7.0950 4.7450
34 2.6450 -7.0950
35 5.0450 2.6450
36 -4.9075 5.0450
37 3.1325 -4.9075
38 5.8125 3.1325
39 -12.2275 5.8125
40 7.5525 -12.2275
41 -0.1875 7.5525
42 -6.6075 -0.1875
43 -0.8075 -6.6075
44 1.6325 -0.8075
45 -0.0075 1.6325
46 4.6325 -0.0075
47 -4.8675 4.6325
48 5.7925 -4.8675
49 -2.1675 5.7925
50 -8.9875 -2.1675
51 -7.1275 -8.9875
52 1.6525 -7.1275
53 5.8125 1.6525
54 2.8925 5.8125
55 1.2925 2.8925
56 -1.5675 1.2925
57 6.2925 -1.5675
58 2.5325 6.2925
59 0.4325 2.5325
60 NA 0.4325
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.6550 -3.8950
[2,] -11.6750 -2.6550
[3,] 4.4850 -11.6750
[4,] -2.7350 4.4850
[5,] -16.7750 -2.7350
[6,] 3.8050 -16.7750
[7,] -11.6950 3.8050
[8,] -8.0550 -11.6950
[9,] -1.0950 -8.0550
[10,] -4.3550 -1.0950
[11,] -1.3550 -4.3550
[12,] -2.0950 -1.3550
[13,] -1.4550 -2.0950
[14,] 8.2250 -1.4550
[15,] 6.9850 8.2250
[16,] -4.1350 6.9850
[17,] 5.2250 -4.1350
[18,] -2.5950 5.2250
[19,] 1.9050 -2.5950
[20,] 3.2450 1.9050
[21,] 1.9050 3.2450
[22,] -5.4550 1.9050
[23,] 0.7450 -5.4550
[24,] 5.1050 0.7450
[25,] 3.1450 5.1050
[26,] 6.6250 3.1450
[27,] 7.8850 6.6250
[28,] -2.3350 7.8850
[29,] 5.9250 -2.3350
[30,] 2.5050 5.9250
[31,] 9.3050 2.5050
[32,] 4.7450 9.3050
[33,] -7.0950 4.7450
[34,] 2.6450 -7.0950
[35,] 5.0450 2.6450
[36,] -4.9075 5.0450
[37,] 3.1325 -4.9075
[38,] 5.8125 3.1325
[39,] -12.2275 5.8125
[40,] 7.5525 -12.2275
[41,] -0.1875 7.5525
[42,] -6.6075 -0.1875
[43,] -0.8075 -6.6075
[44,] 1.6325 -0.8075
[45,] -0.0075 1.6325
[46,] 4.6325 -0.0075
[47,] -4.8675 4.6325
[48,] 5.7925 -4.8675
[49,] -2.1675 5.7925
[50,] -8.9875 -2.1675
[51,] -7.1275 -8.9875
[52,] 1.6525 -7.1275
[53,] 5.8125 1.6525
[54,] 2.8925 5.8125
[55,] 1.2925 2.8925
[56,] -1.5675 1.2925
[57,] 6.2925 -1.5675
[58,] 2.5325 6.2925
[59,] 0.4325 2.5325
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.6550 -3.8950
2 -11.6750 -2.6550
3 4.4850 -11.6750
4 -2.7350 4.4850
5 -16.7750 -2.7350
6 3.8050 -16.7750
7 -11.6950 3.8050
8 -8.0550 -11.6950
9 -1.0950 -8.0550
10 -4.3550 -1.0950
11 -1.3550 -4.3550
12 -2.0950 -1.3550
13 -1.4550 -2.0950
14 8.2250 -1.4550
15 6.9850 8.2250
16 -4.1350 6.9850
17 5.2250 -4.1350
18 -2.5950 5.2250
19 1.9050 -2.5950
20 3.2450 1.9050
21 1.9050 3.2450
22 -5.4550 1.9050
23 0.7450 -5.4550
24 5.1050 0.7450
25 3.1450 5.1050
26 6.6250 3.1450
27 7.8850 6.6250
28 -2.3350 7.8850
29 5.9250 -2.3350
30 2.5050 5.9250
31 9.3050 2.5050
32 4.7450 9.3050
33 -7.0950 4.7450
34 2.6450 -7.0950
35 5.0450 2.6450
36 -4.9075 5.0450
37 3.1325 -4.9075
38 5.8125 3.1325
39 -12.2275 5.8125
40 7.5525 -12.2275
41 -0.1875 7.5525
42 -6.6075 -0.1875
43 -0.8075 -6.6075
44 1.6325 -0.8075
45 -0.0075 1.6325
46 4.6325 -0.0075
47 -4.8675 4.6325
48 5.7925 -4.8675
49 -2.1675 5.7925
50 -8.9875 -2.1675
51 -7.1275 -8.9875
52 1.6525 -7.1275
53 5.8125 1.6525
54 2.8925 5.8125
55 1.2925 2.8925
56 -1.5675 1.2925
57 6.2925 -1.5675
58 2.5325 6.2925
59 0.4325 2.5325
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7esu11229619353.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8f3h01229619353.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9cvar1229619353.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10pzhc1229619353.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/112cin1229619354.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12redv1229619354.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13jege1229619354.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/14jkzj1229619354.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15ssum1229619354.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/160byx1229619354.tab")
+ }
>
> system("convert tmp/1zixj1229619353.ps tmp/1zixj1229619353.png")
> system("convert tmp/2ztyx1229619353.ps tmp/2ztyx1229619353.png")
> system("convert tmp/38w6v1229619353.ps tmp/38w6v1229619353.png")
> system("convert tmp/4y5my1229619353.ps tmp/4y5my1229619353.png")
> system("convert tmp/56k6m1229619353.ps tmp/56k6m1229619353.png")
> system("convert tmp/6quk11229619353.ps tmp/6quk11229619353.png")
> system("convert tmp/7esu11229619353.ps tmp/7esu11229619353.png")
> system("convert tmp/8f3h01229619353.ps tmp/8f3h01229619353.png")
> system("convert tmp/9cvar1229619353.ps tmp/9cvar1229619353.png")
> system("convert tmp/10pzhc1229619353.ps tmp/10pzhc1229619353.png")
>
>
> proc.time()
user system elapsed
2.700 1.747 4.152